the residual is defined as the difference between the actual and predicted, or fitted values of the response variable. group of answer choices false true

The Residual is defined as the difference between the actual and predicted, or fitted values of the response variable. This statement is true.

Linear regression is a statistical tool that determines how well a straight line fits a set of paired data. The straight line that best fits that data is called the least squares regression line. This line can be used in a number of ways. One of these uses is to estimate the value of a response variable for a given value of an explanatory variable. Related to this idea is that of a residual.

Residuals are obtained by performing subtraction. All that we must do is to subtract the predicted value of y from the observed value of y for a particular x. The result is called a residual.

The formula for residuals is straightforward:

Residual = observed y – predicted y

It is important to note that the predicted value comes from our regression line. The observed value comes from our data set.

Residualis defined as the difference between theactualandpredicted, or fitted values of the response variable. This statement is true.Linear regressionis astatisticaltool that determines how well a straight line fits a set ofpaired data.The straight line that best fits that data is called theleast squares regressionline. This line can be used in a number of ways. One of these uses is to estimate the value of a responsevariablefor a given value of anexplanatory variable. Related to this idea is that of a residual.Residualsare obtained by performing subtraction. All that we must do is to subtract thepredicted valueof y from the observed value of y for a particular x. The result is called aresidual.residualsis straightforward:Residual = observed y – predicted ypredicted value comes from ourregression line.The observed value comes from ourdata set.Residual: